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5 Publications
2023 | Published | Journal Article | IST-REx-ID: 14815 | 
Beznosikov, Aleksandr, Samuel Horvath, Peter Richtarik, and Mher Safaryan. “On Biased Compression for Distributed Learning.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2023.
[Published Version]
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| WoS
| arXiv
2022 | Published | Journal Article | IST-REx-ID: 10802 |
Konstantinov, Nikola H, and Christoph Lampert. “Fairness-Aware PAC Learning from Corrupted Data.” Journal of Machine Learning Research. ML Research Press, 2022.
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| arXiv
2022 | Published | Journal Article | IST-REx-ID: 11420 |
Shevchenko, Alexander, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2022.
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| arXiv
2021 | Published | Journal Article | IST-REx-ID: 10180 |
Hoefler, Torsten, Dan-Adrian Alistarh, Tal Ben-Nun, Nikoli Dryden, and Alexandra Krumes. “Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks.” Journal of Machine Learning Research. ML Research Press, 2021.
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| arXiv
2021 | Published | Journal Article | IST-REx-ID: 9571 |
Ramezani-Kebrya, Ali, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan-Adrian Alistarh, and Daniel M. Roy. “NUQSGD: Provably Communication-Efficient Data-Parallel SGD via Nonuniform Quantization.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2021.
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| arXiv